1.6k citations · 12.4k across the 394 of their papers we have counts for
5 papers · 2 filters
Consistent Kernel Mean Estimation for Functions of Random Variables
Carl-Johann Simon-Gabriel, Adam Ścibior, Ilya Tolstikhin +1
We provide a theoretical foundation for non-parametric estimation of functions of random variables using kernel mean embeddings. We show that for any continuous function , consi…
DiSMEC - Distributed Sparse Machines for Extreme Multi-label Classification
Rohit Babbar, Bernhard Shoelkopf
Extreme multi-label classification refers to supervised multi-label learning involving hundreds of thousands or even millions of labels. Datasets in extreme classification exhibit…
Kernel Mean Embedding of Distributions: A Review and Beyond
Krikamol Muandet, Kenji Fukumizu, Bharath Sriperumbudur +1
A Hilbert space embedding of a distribution---in short, a kernel mean embedding---has recently emerged as a powerful tool for machine learning and inference. The basic idea behind…
Discovering Causal Signals in Images
David Lopez-Paz, Robert Nishihara, Soumith Chintala +2
This paper establishes the existence of observable footprints that reveal the "causal dispositions" of the object categories appearing in collections of images. We achieve this goa…
Kernel Distribution Embeddings: Universal Kernels, Characteristic Kernels and Kernel Metrics on Distributions
Carl-Johann Simon-Gabriel, Bernhard Schölkopf
Kernel mean embeddings have recently attracted the attention of the machine learning community. They map measures from some set to functions in a reproducing kernel Hilbert…